It is desirable to be able to non-invasively estimate the tissue blood oxygen saturation (rSO2) level in a human subject's brain. It is known that the cerebral tissue blood oxygen saturation level can be non-invasively estimated using near infrared spectrophotography (NIRS). A system and method for performing spatially resolved NIRS to measure cerebral tissue blood oxygen saturation (rSO2) was disclosed in U.S. Pat. No. 5,139,025, U.S. Pat. No. 5,482,034, and U.S. Pat. No. 5,217,013. In general, those patents describe calculating cerebral tissue blood oxygen saturation (rSO2) as a weighted sum of the venous [HbO2] and arterial [Hb] blood oxygen saturations according to the following equation:rSO2=[HbO2]/([HbO2]+[Hb]).
In the known system and method, a sensor having a light source and two light detectors, each spaced a different distance from the light source, is affixed to the forehead of a human subject. The light detector positioned closer to the source is referred to as the “near” or “shallow” detector and the light detector positioned further from the source is referred to as the “far” or “deep” detector. Light of three different wavelengths is selectively introduced into the subject's head, one wavelength at a time. The optical density (OD) of the reflected light of each wavelength is detected by both the “shallow” and the “deep” detectors. That data is used to calculate a so-called space contrasted ratio of the wavelength contrast difference according to the following equation:OD′Deep-Shall(λ1)/OD′Deep-Shall(λ2)where OD′(λ)=OD(λ)−OD(λ+Δ) is the wavelength contrasted optical density that can be described as a wavelength contrast difference of the optical density OD(λ). In addition, ODDeep-Shall (λ)=ODDeep (λ)−ODShallow (λ) is the spatial contrasted optical density that is the difference of the optical density measured by the far detector ODDeep (λ) and the near detector ODShallow (λ) at wavelength λ. This space contrasted ratio of the wavelength contrast difference can be compared to empirical data to estimate the cerebral tissue blood saturation (rSO2) level of the human subject.
This approach is non-invasive and provides an accurate determination of the rSO2 level of most human subjects. However, it is has been observed that this approach results in invalid rSO2 estimations in approximately 1-2% of human subjects who have normal rSO2 levels, customarily referred to as “outliers.” For outliers, the above-described approach for estimating rSO2 results in a reported estimation that is significantly lower than the person's actual rSO2 level. There is evidence that melanin or a melanin-like (or melanin-based) polymer chromophore localized in the connective tissue that covers the brain may be responsible for outliers. While such polymers that are by products of tyrosine degradation are present in normal individuals, in individuals with alkaptonuria they accumulate excessively in the connective tissues. Depending on the amount of the melanin-like polymers in the brain membranes, the rSO2 baseline measured using the wavelengths can be as low as 15%-20%, significantly less than the average normal rSO2 value of 70%. The presence of other chromophores may also be responsible for outliers.
Additionally, there is evidence that patients with liver disease can have a substantial amount of conjugated bilirubin present in their blood and tissues. While unconjugated bilirubin does not interfere with NIRS measurements, conjugated bilirubin preferentially absorbs in the 700 nm-770 nm range and can adversely affect accuracy of the above-described approach for estimating rSO2.
Accordingly, there is a need for an improved system and method for estimating cerebral tissue oxygen saturation (rSO2) levels in human subjects that is capable of identifying outliers and accurately estimating the cerebral tissue oxygen saturation levels for such outliers.